Computers in Medical Care: A Review

1984 ◽  
Vol 23 (02) ◽  
pp. 63-74 ◽  
Author(s):  
Hans W. Gottinger
Keyword(s):  
Resource Allocation ◽  
Medical Care ◽  
Hospital Care ◽  
The Impact

SummaryThis survey provides an overview of major developments on the impact of computers in medical and hospital care over the last 25 years. Though the review emphasizes developments in the U. S. and their multi-faceted impacts upon resource allocation and regulation, a serious attempt is made to track those impacts being universally true in multinational environments.

The impact of ageing on hospital care and long-term care—the example of Germany

Health Policy ◽  
2004 ◽  
Vol 67 (1) ◽  
pp. 57-74 ◽  
Author(s):  
Erika Schulz ◽  
Reiner Leidl ◽  
Hans-Helmut König
Keyword(s):  
Hospital Care ◽  
Long Term Care ◽  
Term Care ◽  
The Impact

scholarly journals Decreased Medical Care During the COVID-19 Pandemic – A Comprehensive Analysis of Radiological Examinations

2021 ◽  
Author(s):  
Annette Aigner ◽  
Bernd Hamm ◽  
Florian Nima Fleckenstein ◽  
Tazio Maleitzke ◽  
Georg Böning ◽  
...  
Keyword(s):  
Medical Care ◽  
Control Period ◽  
Surrogate Marker ◽  
Medical Specialty ◽  
Case Volume ◽  
Medical Specialties ◽  
Key Points ◽  
Depth Analysis ◽  
The Impact ◽  
Radiological Examinations

Objectives As a cross-section discipline within the hospital infrastructure, radiological departments might be able to provide important information regarding the impact of the COVID-19 pandemic on healthcare. The goal of this study was to quantify changes in medical care during the first wave of the pandemic using radiological examinations as a comprehensive surrogate marker and to determine potential future workload. Methods A retrospective analysis of all radiological examinations during the first wave of the pandemic was performed. The number of examinations was compared to time-matched control periods. Furthermore, an in-depth analysis of radiological examinations attributed to various medical specialties was conducted and postponed examinations were extrapolated to calculate additional workload in the near future. Results A total of 596,760 examinations were analyzed. Overall case volumes decreased by an average of 41 % during the shutdown compared to the control period. The most affected radiological modalities were sonography (–54 %), X-ray (–47 %) followed by MRI (–42 %). The most affected medical specialty was trauma and orthopedics (–60 % case volume) followed by general surgery (–49 %). Examination numbers increased during the post-shutdown period leading to a predicted additional workload of up to 22 %. Conclusion This study shows a marked decrease in radiological examinations in total and among several core medical specialties, indicating a significant reduction in medical care during the first COVID-19 shutdown. Key Points: Citation Format

scholarly journals The impact of predictability on dual-task performance and implications for resource-sharing accounts

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Laura Broeker ◽  
Harald Ewolds ◽  
Rita F. de Oliveira ◽  
Stefan Künzell ◽  
Markus Raab
Keyword(s):  
Resource Allocation ◽  
Task Performance ◽  
Dual Task ◽  
Resource Sharing ◽  
Visual Information ◽  
Allocation Policy ◽  
Capacity Sharing ◽  
Dual Task Performance ◽  
Sound Sequence ◽  
The Impact

AbstractThe aim of this study was to examine the impact of predictability on dual-task performance by systematically manipulating predictability in either one of two tasks, as well as between tasks. According to capacity-sharing accounts of multitasking, assuming a general pool of resources two tasks can draw upon, predictability should reduce the need for resources and allow more resources to be used by the other task. However, it is currently not well understood what drives resource-allocation policy in dual tasks and which resource allocation policies participants pursue. We used a continuous tracking task together with an audiomotor task and manipulated advance visual information about the tracking path in the first experiment and a sound sequence in the second experiments (2a/b). Results show that performance predominantly improved in the predictable task but not in the unpredictable task, suggesting that participants did not invest more resources into the unpredictable task. One possible explanation was that the re-investment of resources into another task requires some relationship between the tasks. Therefore, in the third experiment, we covaried the two tasks by having sounds 250 ms before turning points in the tracking curve. This enabled participants to improve performance in both tasks, suggesting that resources were shared better between tasks.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals How Does Environmental Regulation Affect Industrial Transformation? A Study Based on the Methodology of Policy Simulation

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Wei Liu ◽  
Jian Tong ◽  
Xiaohang Yue
Keyword(s):  
Resource Allocation ◽  
Environmental Regulation ◽  
Spillover Effect ◽  
Policy Simulation ◽  
Industrial Transformation ◽  
Input Structure ◽  
Distortion Effect ◽  
The Difference ◽  
The Impact ◽  
Factor Input

The difference of factor input structure determines different response to environmental regulation. This paper constructs a theoretical model including environmental regulation, factor input structure, and industrial transformation and conducts a policy simulation based on the difference of influencing mechanism of environmental regulation considering industrial heterogeneity. The findings show that the impact of environmental regulation on industrial transformation presents comparison of distortion effect of resource allocation and technology effect. Environmental regulation will promote industrial transformation when technology effect of environmental regulation is stronger than distortion effect of resource allocation. Particularly, command-control environmental regulation has a significant incentive effect and spillover effect of technological innovation on cleaning industries, but these effects do not exist in pollution-intensive industries. Command-control environmental regulation promotes industrial transformation. The result of simulation showed that environmental regulation of market incentives is similar to that of command-control.

scholarly journals Communication as a Key Issue in the Care of Diabetes Mellitus

2015 ◽  
Vol 22 (3) ◽  
pp. 305-310
Author(s):  
Elena-Daniela Grigorescu ◽  
Cristina Mihaela Lăcătuşu ◽  
Gina Eosefina Botnariu ◽  
Raluca Maria Popescu ◽  
Alina Delia Popa ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Medical Care ◽  
Modern Medicine ◽  
Therapeutic Education ◽  
Communicative Interaction ◽  
Patient Centered ◽  
Patient’S Satisfaction ◽  
Communication Techniques ◽  
Physician Patient ◽  
The Impact

Abstract The physician-patient communication has an essential role in establishing and supporting the relationship between these two partners. Moreover, modern medicine highlights the patient-centered approach. Publications assessing the impact of an efficient physicianpatient communication on medical care results in diseases such as diabetes and hypertension have revealed a positive correlation between patient’s satisfaction about the communication with the physician and values of blood pressure, glycated hemoglobin and pain intensity. Interventions needed in both doctors and patients for developing communication abilities were paid special attention in order to achieve an appropriate improvement in their communicative interaction during periodical appointments. In the field of diabetes mellitus, the medical challenge is to improve patients’ knowledge about medical care; this aim is achieved only by therapeutic education, using high-quality communication techniques.

The impact of humanitarian aid on conflict development

1998 ◽  
Vol 38 (323) ◽  
pp. 319-333 ◽  
Author(s):  
Pierre Perrin
Keyword(s):  
Medical Care ◽  
Sharp Increase ◽  
Humanitarian Aid ◽  
Humanitarian Organizations ◽  
The People ◽  
The World ◽  
Local Services ◽  
The Impact

The proliferation of crises around the world has led to a sharp increase in the scale of humanitarian aid required to meet the vital needs of the people affected by them for food, water, medical care and shelter. Humanitarian organizations can either meet those needs directly or support local services engaged in the same work. In most cases, both approaches are used.

AIRA, an Artificial Intelligence Realistic Assistant that will save your time, a before-and-after study during Pandemic (Preprint)

2021 ◽  
Author(s):  
Kaio Bin ◽  
Adler Araújo Ribeiro Melo ◽  
José Guilherme Franco Da Rocha ◽  
Renata Pivi De Almeida ◽  
Vilson Cobello Junior ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Record ◽  
Medical Care ◽  
Health Screening ◽  
Urgent Care ◽  
Health Record ◽  
Before And After ◽  
Electronic Health ◽  
The Impact ◽  
Before And After Study

BACKGROUND AIRA is an AI designed to reduce the time that doctors dedicate filling out EHR, winner of the first edition of MIT Hacking Medicine held in Brazil in 2020. As a proof of concept, AIRA was implemented in administrative process before its application in a medical process. OBJECTIVE The aim of the study is to determinate the impact of AIRA by eliminating the Medical Care Registration (MCR) on Electronic Health Record (EHR) by Administrative Officer. METHODS This is a comparative before-and-after study following the guidance “Evaluating digital health products” from Public Health England. An Artificial Intelligence named AIRA was created and implemented at CEAC (Employee Attention Center) from HCFMUSP. A total of 25,507 attendances were evaluated along 2020 for determinate AIRA´s impact. Total of MCR, time of health screening and time between the end of the screening and the beginning of medical care, were compared in the pre and post AIRA periods. RESULTS AIRA eliminated the need for Medical Care Registration by Administrative Officer in 92% (p<0.0001). The nurse´s time of health screening increased 16% (p<0.0001) during the implementation, and 13% (p<0.0001) until three months after the implementation, but reduced in 4% three months after implementation (p<0.0001). The mean and median total time to Medical Care after the nurse’ Screening was decreased in 30% (p<0.0001) and 41% (p<0.0001) respectively. CONCLUSIONS The implementation of AIRA reduced the time to medical care in an urgent care after the nurse´ screening, by eliminating non-value-added activity the Medical Care Registration on Electronic Health Record (EHR) by Administrative Officer.

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